ArticleBioinformatics (Oxford, England)2011
A probabilistic model of nuclear import of proteins.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- SPSignal: a web tool for structure-assisted prediction of nuclear localization and nuclear export signals in proteins.Nucleic acids research · 2026Article
- Identification of candidate nucleomodulins in ESKAPE bacteria -Frontiers in cellular and infection microbiology · 2026Article
- Nucleomodulins from gut bacteria: diverse mechanisms of translocation and interaction with host nuclear processes.Applied and environmental microbiology · 2025Review
- CanFrontiers in cellular and infection microbiology · 2025Article
- Karyopherin-mediated nucleocytoplasmic transport.Nature reviews. Molecular cell biology · 2022Review
- Tools for the Recognition of Sorting Signals and the Prediction of Subcellular Localization of Proteins From Their Amino Acid Sequences.Frontiers in genetics · 2020Review
- Variations in nuclear localization strategies among pol X family enzymes.Traffic (Copenhagen, Denmark) · 2018Article
- Predicting the dynamics of protein abundance.Molecular & cellular proteomics : MCP · 2014Article
- Dynamics of re-constitution of the human nuclear proteome after cell division is regulated by NLS-adjacent phosphorylation.Cell cycle (Georgetown, Tex.) · 2014Article
- SeqNLS: nuclear localization signal prediction based on frequent pattern mining and linear motif scoring.PloS one · 2013Article
- Mapping the stabilome: a novel computational method for classifying metabolic protein stability.BMC systems biology · 2012Article
- B cell activation triggered by the formation of the small receptor cluster: a computational study.PLoS computational biology · 2011Article
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5 authors.
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Abstract
motivationNucleo-cytoplasmic trafficking of proteins is a core regulatory process that sustains the integrity of the nuclear space of eukaryotic cells via an interplay between numerous factors. Despite progress on experimentally characterizing a number of nuclear localization signals, their presence alone remains an unreliable indicator of actual translocation.
resultsThis article introduces a probabilistic model that explicitly recognizes a variety of nuclear localization signals, and integrates relevant amino acid sequence and interaction data for any candidate nuclear protein. In particular, we develop and incorporate scoring functions based on distinct classes of classical nuclear localization signals. Our empirical results show that the model accurately predicts whether a protein is imported into the nucleus, surpassing the classification accuracy of similar predictors when evaluated on the mouse and yeast proteomes (area under the receiver operator characteristic curve of 0.84 and 0.80, respectively). The model also predicts the sequence position of a nuclear localization signal and whether it interacts with importin-α. AVAILABILITY: http://pprowler.itee.uq.edu.au/NucImport
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